mirror of
https://github.com/explosion/spaCy.git
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fdfdbcd9f4
Also warn when any worker exited with a non-zero exit code and modify test to ensure that workers exit cleanly by default.
1018 lines
66 KiB
Python
1018 lines
66 KiB
Python
import warnings
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from .compat import Literal
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class ErrorsWithCodes(type):
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def __getattribute__(self, code):
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msg = super().__getattribute__(code)
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if code.startswith("__"): # python system attributes like __class__
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return msg
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else:
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return "[{code}] {msg}".format(code=code, msg=msg)
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def setup_default_warnings():
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# ignore certain numpy warnings
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filter_warning("ignore", error_msg="numpy.dtype size changed") # noqa
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filter_warning("ignore", error_msg="numpy.ufunc size changed") # noqa
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# warn about entity_ruler, span_ruler & matcher having no patterns only once
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for pipe in ["matcher", "entity_ruler", "span_ruler"]:
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filter_warning("once", error_msg=Warnings.W036.format(name=pipe))
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# warn once about lemmatizer without required POS
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filter_warning("once", error_msg=Warnings.W108)
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# floret vector table cannot be modified
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filter_warning("once", error_msg="[W114]")
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def filter_warning(
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action: Literal["default", "error", "ignore", "always", "module", "once"],
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error_msg: str,
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):
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"""Customize how spaCy should handle a certain warning.
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error_msg (str): e.g. "W006", or a full error message
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action (str): "default", "error", "ignore", "always", "module" or "once"
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"""
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warnings.filterwarnings(action, message=_escape_warning_msg(error_msg))
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def _escape_warning_msg(msg):
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"""To filter with warnings.filterwarnings, the [] brackets need to be escaped"""
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return msg.replace("[", "\\[").replace("]", "\\]")
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# fmt: off
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class Warnings(metaclass=ErrorsWithCodes):
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W005 = ("Doc object not parsed. This means displaCy won't be able to "
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"generate a dependency visualization for it. Make sure the Doc "
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"was processed with a model that supports dependency parsing, and "
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"not just a language class like `English()`. For more info, see "
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"the docs:\nhttps://spacy.io/usage/models")
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W006 = ("No entities to visualize found in Doc object. If this is "
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"surprising to you, make sure the Doc was processed using a model "
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"that supports named entity recognition, and check the `doc.ents` "
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"property manually if necessary.")
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W007 = ("The model you're using has no word vectors loaded, so the result "
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"of the {obj}.similarity method will be based on the tagger, "
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"parser and NER, which may not give useful similarity judgements. "
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"This may happen if you're using one of the small models, e.g. "
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"`en_core_web_sm`, which don't ship with word vectors and only "
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"use context-sensitive tensors. You can always add your own word "
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"vectors, or use one of the larger models instead if available.")
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W008 = ("Evaluating {obj}.similarity based on empty vectors.")
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W011 = ("It looks like you're calling displacy.serve from within a "
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"Jupyter notebook or a similar environment. This likely means "
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"you're already running a local web server, so there's no need to "
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"make displaCy start another one. Instead, you should be able to "
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"replace displacy.serve with displacy.render to show the "
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"visualization.")
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W012 = ("A Doc object you're adding to the PhraseMatcher for pattern "
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"'{key}' is parsed and/or tagged, but to match on '{attr}', you "
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"don't actually need this information. This means that creating "
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"the patterns is potentially much slower, because all pipeline "
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"components are applied. To only create tokenized Doc objects, "
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"try using `nlp.make_doc(text)` or process all texts as a stream "
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"using `list(nlp.tokenizer.pipe(all_texts))`.")
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W017 = ("Alias '{alias}' already exists in the Knowledge Base.")
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W018 = ("Entity '{entity}' already exists in the Knowledge Base - "
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"ignoring the duplicate entry.")
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W021 = ("Unexpected hash collision in PhraseMatcher. Matches may be "
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"incorrect. Modify PhraseMatcher._terminal_hash to fix.")
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W024 = ("Entity '{entity}' - Alias '{alias}' combination already exists in "
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"the Knowledge Base.")
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W026 = ("Unable to set all sentence boundaries from dependency parses. If "
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"you are constructing a parse tree incrementally by setting "
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"token.head values, you can probably ignore this warning. Consider "
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"using Doc(words, ..., heads=heads, deps=deps) instead.")
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W027 = ("Found a large training file of {size} bytes. Note that it may "
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"be more efficient to split your training data into multiple "
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"smaller JSON files instead.")
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W028 = ("Doc.from_array was called with a vector of type '{type}', "
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"but is expecting one of type uint64 instead. This may result "
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"in problems with the vocab further on in the pipeline.")
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W030 = ("Some entities could not be aligned in the text \"{text}\" with "
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"entities \"{entities}\". Use "
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"`spacy.training.offsets_to_biluo_tags(nlp.make_doc(text), entities)`"
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" to check the alignment. Misaligned entities ('-') will be "
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"ignored during training.")
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W033 = ("Training a new {model} using a model with no lexeme normalization "
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"table. This may degrade the performance of the model to some "
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"degree. If this is intentional or the language you're using "
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"doesn't have a normalization table, please ignore this warning. "
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"If this is surprising, make sure you have the spacy-lookups-data "
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"package installed and load the table in your config. The "
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"languages with lexeme normalization tables are currently: "
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"{langs}\n\nLoad the table in your config with:\n\n"
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"[initialize.lookups]\n"
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"@misc = \"spacy.LookupsDataLoader.v1\"\n"
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"lang = ${{nlp.lang}}\n"
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"tables = [\"lexeme_norm\"]\n")
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W035 = ("Discarding subpattern '{pattern}' due to an unrecognized "
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"attribute or operator.")
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W036 = ("The component '{name}' does not have any patterns defined.")
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# New warnings added in v3.x
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W086 = ("Component '{listener}' will be (re)trained, but it needs the component "
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"'{name}' which is frozen. If you want to prevent retraining '{name}' "
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"but want to train '{listener}' on top of it, you should add '{name}' to the "
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"list of 'annotating_components' in the 'training' block in the config. "
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"See the documentation for details: "
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"https://spacy.io/usage/training#annotating-components")
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W087 = ("Component '{name}' will be (re)trained, but the component '{listener}' "
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"depends on it via a listener and is frozen. This means that the "
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"performance of '{listener}' will be degraded. You can either freeze "
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"both, or neither of the two. If you're sourcing the component from "
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"an existing pipeline, you can use the `replace_listeners` setting in "
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"the config block to replace its token-to-vector listener with a copy "
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"and make it independent. For example, `replace_listeners = "
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"[\"model.tok2vec\"]` See the documentation for details: "
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"https://spacy.io/usage/training#config-components-listeners")
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W088 = ("The pipeline component {name} implements a `begin_training` "
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"method, which won't be called by spaCy. As of v3.0, `begin_training` "
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"has been renamed to `initialize`, so you likely want to rename the "
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"component method. See the documentation for details: "
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"https://spacy.io/api/language#initialize")
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W089 = ("As of spaCy v3.0, the `nlp.begin_training` method has been renamed "
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"to `nlp.initialize`.")
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W090 = ("Could not locate any {format} files in path '{path}'.")
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W091 = ("Could not clean/remove the temp directory at {dir}: {msg}.")
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W092 = ("Ignoring annotations for sentence starts, as dependency heads are set.")
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W093 = ("Could not find any data to train the {name} on. Is your "
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"input data correctly formatted?")
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W094 = ("Model '{model}' ({model_version}) specifies an under-constrained "
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"spaCy version requirement: {version}. This can lead to compatibility "
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"problems with older versions, or as new spaCy versions are "
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"released, because the model may say it's compatible when it's "
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'not. Consider changing the "spacy_version" in your meta.json to a '
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"version range, with a lower and upper pin. For example: {example}")
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W095 = ("Model '{model}' ({model_version}) was trained with spaCy "
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"{version} and may not be 100% compatible with the current version "
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"({current}). If you see errors or degraded performance, download "
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"a newer compatible model or retrain your custom model with the "
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"current spaCy version. For more details and available updates, "
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"run: python -m spacy validate")
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W096 = ("The method `nlp.disable_pipes` is now deprecated - use "
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"`nlp.select_pipes` instead.")
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W100 = ("Skipping unsupported morphological feature(s): '{feature}'. "
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"Provide features as a dict {{\"Field1\": \"Value1,Value2\"}} or "
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"string \"Field1=Value1,Value2|Field2=Value3\".")
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W101 = ("Skipping Doc custom extension '{name}' while merging docs.")
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W102 = ("Skipping unsupported user data '{key}: {value}' while merging docs.")
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W103 = ("Unknown {lang} word segmenter '{segmenter}'. Supported "
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"word segmenters: {supported}. Defaulting to {default}.")
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W104 = ("Skipping modifications for '{target}' segmenter. The current "
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"segmenter is '{current}'.")
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W105 = ("As of spaCy v3.0, the `{matcher}.pipe` method is deprecated. If you "
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"need to match on a stream of documents, you can use `nlp.pipe` and "
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"call the {matcher} on each Doc object.")
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W107 = ("The property `Doc.{prop}` is deprecated. Use "
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"`Doc.has_annotation(\"{attr}\")` instead.")
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W108 = ("The rule-based lemmatizer did not find POS annotation for one or "
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"more tokens. Check that your pipeline includes components that "
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"assign token.pos, typically 'tagger'+'attribute_ruler' or "
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"'morphologizer'.")
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W109 = ("Unable to save user hooks while serializing the doc. Re-add any "
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"required user hooks to the doc after processing.")
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W110 = ("The DependencyMatcher token pattern {pattern} matched a span "
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"{tokens} that is 2+ tokens long. Only the first token in the span "
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"will be included in the results. For better results, token "
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"patterns should return matches that are each exactly one token "
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"long.")
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W111 = ("Jupyter notebook detected: if using `prefer_gpu()` or "
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"`require_gpu()`, include it in the same cell right before "
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"`spacy.load()` to ensure that the model is loaded on the correct "
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"device. More information: "
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"http://spacy.io/usage/v3#jupyter-notebook-gpu")
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W112 = ("The model specified to use for initial vectors ({name}) has no "
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"vectors. This is almost certainly a mistake.")
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W113 = ("Sourced component '{name}' may not work as expected: source "
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"vectors are not identical to current pipeline vectors.")
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W114 = ("Using multiprocessing with GPU models is not recommended and may "
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"lead to errors.")
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W115 = ("Skipping {method}: the floret vector table cannot be modified. "
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"Vectors are calculated from character ngrams.")
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W116 = ("Unable to clean attribute '{attr}'.")
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W117 = ("No spans to visualize found in Doc object with spans_key: '{spans_key}'. If this is "
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"surprising to you, make sure the Doc was processed using a model "
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"that supports span categorization, and check the `doc.spans[spans_key]` "
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"property manually if necessary.\n\nAvailable keys: {keys}")
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W118 = ("Term '{term}' not found in glossary. It may however be explained in documentation "
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"for the corpora used to train the language. Please check "
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"`nlp.meta[\"sources\"]` for any relevant links.")
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W119 = ("Overriding pipe name in `config` is not supported. Ignoring override '{name_in_config}'.")
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W120 = ("Unable to load all spans in Doc.spans: more than one span group "
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"with the name '{group_name}' was found in the saved spans data. "
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"Only the last span group will be loaded under "
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"Doc.spans['{group_name}']. Skipping span group with values: "
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"{group_values}")
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W121 = ("Attempting to trace non-existent method '{method}' in pipe '{pipe}'")
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W122 = ("Couldn't trace method '{method}' in pipe '{pipe}'. This can happen if the pipe class "
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"is a Cython extension type.")
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W123 = ("Argument `enable` with value {enable} does not contain all values specified in the config option "
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"`enabled` ({enabled}). Be aware that this might affect other components in your pipeline.")
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W124 = ("{host}:{port} is already in use, using the nearest available port {serve_port} as an alternative.")
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W125 = ("The StaticVectors key_attr is no longer used. To set a custom "
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"key attribute for vectors, configure it through Vectors(attr=) or "
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"'spacy init vectors --attr'")
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W126 = ("These keys are unsupported: {unsupported}")
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W127 = ("Not all `Language.pipe` worker processes completed successfully")
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class Errors(metaclass=ErrorsWithCodes):
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E001 = ("No component '{name}' found in pipeline. Available names: {opts}")
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E002 = ("Can't find factory for '{name}' for language {lang} ({lang_code}). "
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"This usually happens when spaCy calls `nlp.{method}` with a custom "
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"component name that's not registered on the current language class. "
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"If you're using a custom component, make sure you've added the "
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"decorator `@Language.component` (for function components) or "
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"`@Language.factory` (for class components).\n\nAvailable "
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"factories: {opts}")
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E003 = ("Not a valid pipeline component. Expected callable, but "
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"got {component} (name: '{name}'). If you're using a custom "
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"component factory, double-check that it correctly returns your "
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"initialized component.")
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E004 = ("Can't set up pipeline component: a factory for '{name}' already "
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"exists. Existing factory: {func}. New factory: {new_func}")
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E005 = ("Pipeline component '{name}' returned {returned_type} instead of a "
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"Doc. If you're using a custom component, maybe you forgot to "
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"return the processed Doc?")
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E006 = ("Invalid constraints for adding pipeline component. You can only "
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"set one of the following: before (component name or index), "
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"after (component name or index), first (True) or last (True). "
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"Invalid configuration: {args}. Existing components: {opts}")
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E007 = ("'{name}' already exists in pipeline. Existing names: {opts}")
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E008 = ("Can't restore disabled pipeline component '{name}' because it "
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"doesn't exist in the pipeline anymore. If you want to remove "
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"components from the pipeline, you should do it before calling "
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"`nlp.select_pipes` or after restoring the disabled components.")
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E010 = ("Word vectors set to length 0. This may be because you don't have "
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"a model installed or loaded, or because your model doesn't "
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"include word vectors. For more info, see the docs:\n"
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"https://spacy.io/usage/models")
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E011 = ("Unknown operator: '{op}'. Options: {opts}")
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E012 = ("Cannot add pattern for zero tokens to matcher.\nKey: {key}")
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E016 = ("MultitaskObjective target should be function or one of: dep, "
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"tag, ent, dep_tag_offset, ent_tag.")
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E017 = ("Can only add unicode or bytes. Got type: {value_type}")
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E018 = ("Can't retrieve string for hash '{hash_value}'. This usually "
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"refers to an issue with the `Vocab` or `StringStore`.")
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E019 = ("Can't create transition with unknown action ID: {action}. Action "
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"IDs are enumerated in spacy/syntax/{src}.pyx.")
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E022 = ("Could not find a transition with the name '{name}' in the NER "
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"model.")
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E024 = ("Could not find an optimal move to supervise the parser. Usually, "
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"this means that the model can't be updated in a way that's valid "
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"and satisfies the correct annotations specified in the GoldParse. "
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"For example, are all labels added to the model? If you're "
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"training a named entity recognizer, also make sure that none of "
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"your annotated entity spans have leading or trailing whitespace "
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"or punctuation. You can also use the `debug data` command to "
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"validate your JSON-formatted training data. For details, run:\n"
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"python -m spacy debug data --help")
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E025 = ("String is too long: {length} characters. Max is 2**30.")
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E026 = ("Error accessing token at position {i}: out of bounds in Doc of "
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"length {length}.")
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E027 = ("Arguments `words` and `spaces` should be sequences of the same "
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"length, or `spaces` should be left default at None. `spaces` "
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"should be a sequence of booleans, with True meaning that the "
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"word owns a ' ' character following it.")
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E028 = ("`words` expects a list of unicode strings, but got bytes instance: {value}")
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E029 = ("`noun_chunks` requires the dependency parse, which requires a "
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"statistical model to be installed and loaded. For more info, see "
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"the documentation:\nhttps://spacy.io/usage/models")
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E030 = ("Sentence boundaries unset. You can add the 'sentencizer' "
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"component to the pipeline with: `nlp.add_pipe('sentencizer')`. "
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"Alternatively, add the dependency parser or sentence recognizer, "
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"or set sentence boundaries by setting `doc[i].is_sent_start`.")
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E031 = ("Invalid token: empty string ('') at position {i}.")
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E033 = ("Cannot load into non-empty Doc of length {length}.")
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E035 = ("Error creating span with start {start} and end {end} for Doc of "
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"length {length}.")
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E036 = ("Error calculating span: Can't find a token starting at character "
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"offset {start}.")
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E037 = ("Error calculating span: Can't find a token ending at character "
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"offset {end}.")
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E039 = ("Array bounds exceeded while searching for root word. This likely "
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"means the parse tree is in an invalid state. Please report this "
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"issue here: http://github.com/explosion/spaCy/issues")
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E040 = ("Attempt to access token at {i}, max length {max_length}.")
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E041 = ("Invalid comparison operator: {op}. Likely a Cython bug?")
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E042 = ("Error accessing `doc[{i}].nbor({j})`, for doc of length {length}.")
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E043 = ("Refusing to write to token.sent_start if its document is parsed, "
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"because this may cause inconsistent state.")
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E044 = ("Invalid value for token.sent_start: {value}. Must be one of: "
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"None, True, False")
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E045 = ("Possibly infinite loop encountered while looking for {attr}.")
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E046 = ("Can't retrieve unregistered extension attribute '{name}'. Did "
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"you forget to call the `set_extension` method?")
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E047 = ("Can't assign a value to unregistered extension attribute "
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"'{name}'. Did you forget to call the `set_extension` method?")
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E048 = ("Can't import language {lang} or any matching language from spacy.lang: {err}")
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E050 = ("Can't find model '{name}'. It doesn't seem to be a Python "
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"package or a valid path to a data directory.")
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E052 = ("Can't find model directory: {path}")
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E053 = ("Could not read {name} from {path}")
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E054 = ("No valid '{setting}' setting found in model meta.json.")
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E055 = ("Invalid ORTH value in exception:\nKey: {key}\nOrths: {orths}")
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E056 = ("Invalid tokenizer exception: ORTH values combined don't match "
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"original string.\nKey: {key}\nOrths: {orths}")
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E057 = ("Stepped slices not supported in Span objects. Try: "
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"`list(tokens)[start:stop:step]` instead.")
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E058 = ("Could not retrieve vector for key {key}.")
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E059 = ("One (and only one) keyword arg must be set. Got: {kwargs}")
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E060 = ("Cannot add new key to vectors: the table is full. Current shape: "
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"({rows}, {cols}).")
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E062 = ("Cannot find empty bit for new lexical flag. All bits between 0 "
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"and 63 are occupied. You can replace one by specifying the "
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"`flag_id` explicitly, e.g. "
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"`nlp.vocab.add_flag(your_func, flag_id=IS_ALPHA`.")
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E063 = ("Invalid value for `flag_id`: {value}. Flag IDs must be between 1 "
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"and 63 (inclusive).")
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E064 = ("Error fetching a Lexeme from the Vocab. When looking up a "
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"string, the lexeme returned had an orth ID that did not match "
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"the query string. This means that the cached lexeme structs are "
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"mismatched to the string encoding table. The mismatched:\n"
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"Query string: {string}\nOrth cached: {orth}\nOrth ID: {orth_id}")
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E065 = ("Only one of the vector table's width and shape can be specified. "
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"Got width {width} and shape {shape}.")
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E067 = ("Invalid BILUO tag sequence: Got a tag starting with {start} "
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"without a preceding 'B' (beginning of an entity). "
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"Tag sequence:\n{tags}")
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E068 = ("Invalid BILUO tag: '{tag}'.")
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E071 = ("Error creating lexeme: specified orth ID ({orth}) does not "
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"match the one in the vocab ({vocab_orth}).")
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E073 = ("Cannot assign vector of length {new_length}. Existing vectors "
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"are of length {length}. You can use `vocab.reset_vectors` to "
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"clear the existing vectors and resize the table.")
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E074 = ("Error interpreting compiled match pattern: patterns are expected "
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"to end with the attribute {attr}. Got: {bad_attr}.")
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E079 = ("Error computing states in beam: number of predicted beams "
|
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"({pbeams}) does not equal number of gold beams ({gbeams}).")
|
|
E080 = ("Duplicate state found in beam: {key}.")
|
|
E081 = ("Error getting gradient in beam: number of histories ({n_hist}) "
|
|
"does not equal number of losses ({losses}).")
|
|
E082 = ("Error deprojectivizing parse: number of heads ({n_heads}), "
|
|
"projective heads ({n_proj_heads}) and labels ({n_labels}) do not "
|
|
"match.")
|
|
E083 = ("Error setting extension: only one of `default`, `method`, or "
|
|
"`getter` (plus optional `setter`) is allowed. Got: {nr_defined}")
|
|
E084 = ("Error assigning label ID {label} to span: not in StringStore.")
|
|
E085 = ("Can't create lexeme for string '{string}'.")
|
|
E087 = ("Unknown displaCy style: {style}.")
|
|
E088 = ("Text of length {length} exceeds maximum of {max_length}. The "
|
|
"parser and NER models require roughly 1GB of temporary "
|
|
"memory per 100,000 characters in the input. This means long "
|
|
"texts may cause memory allocation errors. If you're not using "
|
|
"the parser or NER, it's probably safe to increase the "
|
|
"`nlp.max_length` limit. The limit is in number of characters, so "
|
|
"you can check whether your inputs are too long by checking "
|
|
"`len(text)`.")
|
|
E089 = ("Extensions can't have a setter argument without a getter "
|
|
"argument. Check the keyword arguments on `set_extension`.")
|
|
E090 = ("Extension '{name}' already exists on {obj}. To overwrite the "
|
|
"existing extension, set `force=True` on `{obj}.set_extension`.")
|
|
E091 = ("Invalid extension attribute {name}: expected callable or None, "
|
|
"but got: {value}")
|
|
E093 = ("token.ent_iob values make invalid sequence: I without B\n{seq}")
|
|
E094 = ("Error reading line {line_num} in vectors file {loc}.")
|
|
E095 = ("Can't write to frozen dictionary. This is likely an internal "
|
|
"error. Are you writing to a default function argument?")
|
|
E096 = ("Invalid object passed to displaCy: Can only visualize `Doc` or "
|
|
"Span objects, or dicts if set to `manual=True`.")
|
|
E097 = ("Invalid pattern: expected token pattern (list of dicts) or "
|
|
"phrase pattern (string) but got:\n{pattern}")
|
|
E098 = ("Invalid pattern: expected both RIGHT_ID and RIGHT_ATTRS.")
|
|
E099 = ("Invalid pattern: the first node of pattern should be an anchor "
|
|
"node. The node should only contain RIGHT_ID and RIGHT_ATTRS.")
|
|
E100 = ("Nodes other than the anchor node should all contain {required}, "
|
|
"but these are missing: {missing}")
|
|
E101 = ("RIGHT_ID should be a new node and LEFT_ID should already have "
|
|
"have been declared in previous edges.")
|
|
E102 = ("Can't merge non-disjoint spans. '{token}' is already part of "
|
|
"tokens to merge. If you want to find the longest non-overlapping "
|
|
"spans, you can use the util.filter_spans helper:\n"
|
|
"https://spacy.io/api/top-level#util.filter_spans")
|
|
E103 = ("Trying to set conflicting doc.ents: '{span1}' and '{span2}'. A "
|
|
"token can only be part of one entity, so make sure the entities "
|
|
"you're setting don't overlap. To work with overlapping entities, "
|
|
"consider using doc.spans instead.")
|
|
E106 = ("Can't find `doc._.{attr}` attribute specified in the underscore "
|
|
"settings: {opts}")
|
|
E107 = ("Value of custom attribute `{attr}` is not JSON-serializable: {value}")
|
|
E109 = ("Component '{name}' could not be run. Did you forget to "
|
|
"call `initialize()`?")
|
|
E110 = ("Invalid displaCy render wrapper. Expected callable, got: {obj}")
|
|
E111 = ("Pickling a token is not supported, because tokens are only views "
|
|
"of the parent Doc and can't exist on their own. A pickled token "
|
|
"would always have to include its Doc and Vocab, which has "
|
|
"practically no advantage over pickling the parent Doc directly. "
|
|
"So instead of pickling the token, pickle the Doc it belongs to.")
|
|
E112 = ("Pickling a span is not supported, because spans are only views "
|
|
"of the parent Doc and can't exist on their own. A pickled span "
|
|
"would always have to include its Doc and Vocab, which has "
|
|
"practically no advantage over pickling the parent Doc directly. "
|
|
"So instead of pickling the span, pickle the Doc it belongs to or "
|
|
"use Span.as_doc to convert the span to a standalone Doc object.")
|
|
E115 = ("All subtokens must have associated heads.")
|
|
E117 = ("The newly split tokens must match the text of the original token. "
|
|
"New orths: {new}. Old text: {old}.")
|
|
E118 = ("The custom extension attribute '{attr}' is not registered on the "
|
|
"`Token` object so it can't be set during retokenization. To "
|
|
"register an attribute, use the `Token.set_extension` classmethod.")
|
|
E119 = ("Can't set custom extension attribute '{attr}' during "
|
|
"retokenization because it's not writable. This usually means it "
|
|
"was registered with a getter function (and no setter) or as a "
|
|
"method extension, so the value is computed dynamically. To "
|
|
"overwrite a custom attribute manually, it should be registered "
|
|
"with a default value or with a getter AND setter.")
|
|
E120 = ("Can't set custom extension attributes during retokenization. "
|
|
"Expected dict mapping attribute names to values, but got: {value}")
|
|
E121 = ("Can't bulk merge spans. Attribute length {attr_len} should be "
|
|
"equal to span length ({span_len}).")
|
|
E122 = ("Cannot find token to be split. Did it get merged?")
|
|
E123 = ("Cannot find head of token to be split. Did it get merged?")
|
|
E125 = ("Unexpected value: {value}")
|
|
E126 = ("Unexpected matcher predicate: '{bad}'. Expected one of: {good}. "
|
|
"This is likely a bug in spaCy, so feel free to open an issue.")
|
|
E130 = ("You are running a narrow unicode build, which is incompatible "
|
|
"with spacy >= 2.1.0. To fix this, reinstall Python and use a wide "
|
|
"unicode build instead. You can also rebuild Python and set the "
|
|
"`--enable-unicode=ucs4 flag`.")
|
|
E132 = ("The vectors for entities and probabilities for alias '{alias}' "
|
|
"should have equal length, but found {entities_length} and "
|
|
"{probabilities_length} respectively.")
|
|
E133 = ("The sum of prior probabilities for alias '{alias}' should not "
|
|
"exceed 1, but found {sum}.")
|
|
E134 = ("Entity '{entity}' is not defined in the Knowledge Base.")
|
|
E139 = ("Knowledge base for component '{name}' is empty.")
|
|
E140 = ("The list of entities, prior probabilities and entity vectors "
|
|
"should be of equal length.")
|
|
E141 = ("Entity vectors should be of length {required} instead of the "
|
|
"provided {found}.")
|
|
E143 = ("Labels for component '{name}' not initialized. This can be fixed "
|
|
"by calling add_label, or by providing a representative batch of "
|
|
"examples to the component's `initialize` method.")
|
|
E145 = ("Error reading `{param}` from input file.")
|
|
E146 = ("Could not access {path}.")
|
|
E147 = ("Unexpected error in the {method} functionality of the "
|
|
"EntityLinker: {msg}. This is likely a bug in spaCy, so feel free "
|
|
"to open an issue: https://github.com/explosion/spaCy/issues")
|
|
E148 = ("Expected {ents} KB identifiers but got {ids}. Make sure that "
|
|
"each entity in `doc.ents` is assigned to a KB identifier.")
|
|
E149 = ("Error deserializing model. Check that the config used to create "
|
|
"the component matches the model being loaded.")
|
|
E150 = ("The language of the `nlp` object and the `vocab` should be the "
|
|
"same, but found '{nlp}' and '{vocab}' respectively.")
|
|
E152 = ("The attribute {attr} is not supported for token patterns. "
|
|
"Please use the option `validate=True` with the Matcher, PhraseMatcher, "
|
|
"EntityRuler or AttributeRuler for more details.")
|
|
E153 = ("The value type {vtype} is not supported for token patterns. "
|
|
"Please use the option validate=True with Matcher, PhraseMatcher, "
|
|
"EntityRuler or AttributeRuler for more details.")
|
|
E154 = ("One of the attributes or values is not supported for token "
|
|
"patterns. Please use the option `validate=True` with the Matcher, "
|
|
"PhraseMatcher, or EntityRuler for more details.")
|
|
E155 = ("The pipeline needs to include a {pipe} in order to use "
|
|
"Matcher or PhraseMatcher with the attribute {attr}. "
|
|
"Try using `nlp()` instead of `nlp.make_doc()` or `list(nlp.pipe())` "
|
|
"instead of `list(nlp.tokenizer.pipe())`.")
|
|
E157 = ("Can't render negative values for dependency arc start or end. "
|
|
"Make sure that you're passing in absolute token indices, not "
|
|
"relative token offsets.\nstart: {start}, end: {end}, label: "
|
|
"{label}, direction: {dir}")
|
|
E158 = ("Can't add table '{name}' to lookups because it already exists.")
|
|
E159 = ("Can't find table '{name}' in lookups. Available tables: {tables}")
|
|
E160 = ("Can't find language data file: {path}")
|
|
E161 = ("Found an internal inconsistency when predicting entity links. "
|
|
"This is likely a bug in spaCy, so feel free to open an issue: "
|
|
"https://github.com/explosion/spaCy/issues")
|
|
E163 = ("cumsum was found to be unstable: its last element does not "
|
|
"correspond to sum")
|
|
E164 = ("x is neither increasing nor decreasing: {x}.")
|
|
E165 = ("Only one class present in the gold labels: {label}. "
|
|
"ROC AUC score is not defined in that case.")
|
|
E166 = ("Can only merge DocBins with the same value for '{param}'.\n"
|
|
"Current DocBin: {current}\nOther DocBin: {other}")
|
|
E169 = ("Can't find module: {module}")
|
|
E170 = ("Cannot apply transition {name}: invalid for the current state.")
|
|
E171 = ("Matcher.add received invalid 'on_match' callback argument: expected "
|
|
"callable or None, but got: {arg_type}")
|
|
E175 = ("Can't remove rule for unknown match pattern ID: {key}")
|
|
E176 = ("Alias '{alias}' is not defined in the Knowledge Base.")
|
|
E177 = ("Ill-formed IOB input detected: {tag}")
|
|
E178 = ("Each pattern should be a list of dicts, but got: {pat}. Maybe you "
|
|
"accidentally passed a single pattern to Matcher.add instead of a "
|
|
"list of patterns? If you only want to add one pattern, make sure "
|
|
"to wrap it in a list. For example: `matcher.add('{key}', [pattern])`")
|
|
E179 = ("Invalid pattern. Expected a list of Doc objects but got a single "
|
|
"Doc. If you only want to add one pattern, make sure to wrap it "
|
|
"in a list. For example: `matcher.add('{key}', [doc])`")
|
|
E180 = ("Span attributes can't be declared as required or assigned by "
|
|
"components, since spans are only views of the Doc. Use Doc and "
|
|
"Token attributes (or custom extension attributes) only and remove "
|
|
"the following: {attrs}")
|
|
E181 = ("Received invalid attributes for unknown object {obj}: {attrs}. "
|
|
"Only Doc and Token attributes are supported.")
|
|
E182 = ("Received invalid attribute declaration: {attr}\nDid you forget "
|
|
"to define the attribute? For example: `{attr}.???`")
|
|
E183 = ("Received invalid attribute declaration: {attr}\nOnly top-level "
|
|
"attributes are supported, for example: {solution}")
|
|
E184 = ("Only attributes without underscores are supported in component "
|
|
"attribute declarations (because underscore and non-underscore "
|
|
"attributes are connected anyways): {attr} -> {solution}")
|
|
E185 = ("Received invalid attribute in component attribute declaration: "
|
|
"`{obj}.{attr}`\nAttribute '{attr}' does not exist on {obj}.")
|
|
E187 = ("Only unicode strings are supported as labels.")
|
|
E189 = ("Each argument to `Doc.__init__` should be of equal length.")
|
|
E190 = ("Token head out of range in `Doc.from_array()` for token index "
|
|
"'{index}' with value '{value}' (equivalent to relative head "
|
|
"index: '{rel_head_index}'). The head indices should be relative "
|
|
"to the current token index rather than absolute indices in the "
|
|
"array.")
|
|
E191 = ("Invalid head: the head token must be from the same doc as the "
|
|
"token itself.")
|
|
E192 = ("Unable to resize vectors in place with cupy.")
|
|
E193 = ("Unable to resize vectors in place if the resized vector dimension "
|
|
"({new_dim}) is not the same as the current vector dimension "
|
|
"({curr_dim}).")
|
|
E194 = ("Unable to aligned mismatched text '{text}' and words '{words}'.")
|
|
E195 = ("Matcher can be called on {good} only, got {got}.")
|
|
E196 = ("Refusing to write to `token.is_sent_end`. Sentence boundaries can "
|
|
"only be fixed with `token.is_sent_start`.")
|
|
E197 = ("Row out of bounds, unable to add row {row} for key {key}.")
|
|
E198 = ("Unable to return {n} most similar vectors for the current vectors "
|
|
"table, which contains {n_rows} vectors.")
|
|
E199 = ("Unable to merge 0-length span at `doc[{start}:{end}]`.")
|
|
E200 = ("Can't set {attr} from Span.")
|
|
E202 = ("Unsupported {name} mode '{mode}'. Supported modes: {modes}.")
|
|
E203 = ("If the {name} embedding layer is not updated "
|
|
"during training, make sure to include it in 'annotating components'")
|
|
|
|
# New errors added in v3.x
|
|
E849 = ("The vocab only supports {method} for vectors of type "
|
|
"spacy.vectors.Vectors, not {vectors_type}.")
|
|
E850 = ("The PretrainVectors objective currently only supports default or "
|
|
"floret vectors, not {mode} vectors.")
|
|
E851 = ("The 'textcat' component labels should only have values of 0 or 1, "
|
|
"but found value of '{val}'.")
|
|
E853 = ("Unsupported component factory name '{name}'. The character '.' is "
|
|
"not permitted in factory names.")
|
|
E854 = ("Unable to set doc.ents. Check that the 'ents_filter' does not "
|
|
"permit overlapping spans.")
|
|
E855 = ("Invalid {obj}: {obj} is not from the same doc.")
|
|
E856 = ("Error accessing span at position {i}: out of bounds in span group "
|
|
"of length {length}.")
|
|
E857 = ("Entry '{name}' not found in edit tree lemmatizer labels.")
|
|
E858 = ("The {mode} vector table does not support this operation. "
|
|
"{alternative}")
|
|
E859 = ("The floret vector table cannot be modified.")
|
|
E860 = ("Can't truncate floret vectors.")
|
|
E861 = ("No 'keys' should be provided when initializing floret vectors "
|
|
"with 'minn' and 'maxn'.")
|
|
E862 = ("'hash_count' must be between 1-4 for floret vectors.")
|
|
E863 = ("'maxn' must be greater than or equal to 'minn'.")
|
|
E864 = ("The complete vector table 'data' is required to initialize floret "
|
|
"vectors.")
|
|
E865 = ("A SpanGroup is not functional after the corresponding Doc has "
|
|
"been garbage collected. To keep using the spans, make sure that "
|
|
"the corresponding Doc object is still available in the scope of "
|
|
"your function.")
|
|
E866 = ("Expected a string or 'Doc' as input, but got: {type}.")
|
|
E867 = ("The 'textcat' component requires at least two labels because it "
|
|
"uses mutually exclusive classes where exactly one label is True "
|
|
"for each doc. For binary classification tasks, you can use two "
|
|
"labels with 'textcat' (LABEL / NOT_LABEL) or alternatively, you "
|
|
"can use the 'textcat_multilabel' component with one label.")
|
|
E868 = ("Found a conflicting gold annotation in a reference document, "
|
|
"with the following char-based span occurring both in the gold ents "
|
|
"as well as in the negative spans: {span}.")
|
|
E869 = ("The notation '{label}' is not supported anymore. To annotate "
|
|
"negative NER samples, use `doc.spans[key]` instead, and "
|
|
"specify the key as 'incorrect_spans_key' when constructing "
|
|
"the NER component.")
|
|
E870 = ("Could not serialize the DocBin because it is too large. Consider "
|
|
"splitting up your documents into several doc bins and serializing "
|
|
"each separately. spacy.Corpus.v1 will search recursively for all "
|
|
"*.spacy files if you provide a directory instead of a filename as "
|
|
"the 'path'.")
|
|
E871 = ("Error encountered in nlp.pipe with multiprocessing:\n\n{error}")
|
|
E872 = ("Unable to copy tokenizer from base model due to different "
|
|
'tokenizer settings: current tokenizer config "{curr_config}" '
|
|
'vs. base model "{base_config}"')
|
|
E873 = ("Unable to merge a span from doc.spans with key '{key}' and text "
|
|
"'{text}'. This is likely a bug in spaCy, so feel free to open an "
|
|
"issue: https://github.com/explosion/spaCy/issues")
|
|
E874 = ("Could not initialize the tok2vec model from component "
|
|
"'{component}' and layer '{layer}'.")
|
|
E875 = ("To use the PretrainVectors objective, make sure that static vectors are loaded. "
|
|
"In the config, these are defined by the initialize.vectors setting.")
|
|
E879 = ("Unexpected type for 'spans' data. Provide a dictionary mapping keys to "
|
|
"a list of spans, with each span represented by a tuple (start_char, end_char). "
|
|
"The tuple can be optionally extended with a label and a KB ID.")
|
|
E884 = ("The pipeline could not be initialized because the vectors "
|
|
"could not be found at '{vectors}'. If your pipeline was already "
|
|
"initialized/trained before, call 'resume_training' instead of 'initialize', "
|
|
"or initialize only the components that are new.")
|
|
E885 = ("entity_linker.set_kb received an invalid 'kb_loader' argument: expected "
|
|
"a callable function, but got: {arg_type}")
|
|
E886 = ("Can't replace {name} -> {tok2vec} listeners: path '{path}' not "
|
|
"found in config for component '{name}'.")
|
|
E887 = ("Can't replace {name} -> {tok2vec} listeners: the paths to replace "
|
|
"({paths}) don't match the available listeners in the model ({n_listeners}).")
|
|
E888 = ("Can't replace listeners for '{name}' ({pipe}): invalid upstream "
|
|
"component that doesn't seem to support listeners. Expected Tok2Vec "
|
|
"or Transformer component. If you didn't call nlp.replace_listeners "
|
|
"manually, this is likely a bug in spaCy.")
|
|
E889 = ("Can't replace '{tok2vec}' listeners of component '{name}' because "
|
|
"'{unknown}' is not in the pipeline. Available components: {opts}. "
|
|
"If you didn't call nlp.replace_listeners manually, this is likely "
|
|
"a bug in spaCy.")
|
|
E890 = ("Cannot add the alias '{alias}' to the Knowledge base. "
|
|
"Each alias should be a meaningful string.")
|
|
E891 = ("Alias '{alias}' could not be added to the Knowledge base. "
|
|
"This is likely a bug in spaCy.")
|
|
E892 = ("Unknown function registry: '{name}'.\n\nAvailable names: {available}")
|
|
E893 = ("Could not find function '{name}' in function registry '{reg_name}'. "
|
|
"If you're using a custom function, make sure the code is available. "
|
|
"If the function is provided by a third-party package, e.g. "
|
|
"spacy-transformers, make sure the package is installed in your "
|
|
"environment.\n\nAvailable names: {available}")
|
|
E894 = ("The 'noun_chunks' syntax iterator is not implemented for language "
|
|
"'{lang}'.")
|
|
E895 = ("The 'textcat' component received gold-standard annotations with "
|
|
"multiple labels per document. In spaCy 3 you should use the "
|
|
"'textcat_multilabel' component for this instead. "
|
|
"Example of an offending annotation: {value}")
|
|
E896 = ("There was an error using the static vectors. Ensure that the vectors "
|
|
"of the vocab are properly initialized, or set 'include_static_vectors' "
|
|
"to False.")
|
|
E897 = ("Field '{field}' should be a dot-notation string referring to the "
|
|
"relevant section in the config, but found type {type} instead.")
|
|
E898 = ("Can't serialize trainable pipe '{name}': the `model` attribute "
|
|
"is not set or None. If you've implemented a custom component, make "
|
|
"sure to store the component model as `self.model` in your "
|
|
"component's __init__ method.")
|
|
E899 = ("Can't serialize trainable pipe '{name}': the `vocab` attribute "
|
|
"is not set or None. If you've implemented a custom component, make "
|
|
"sure to store the current `nlp` object's vocab as `self.vocab` in "
|
|
"your component's __init__ method.")
|
|
E900 = ("Could not run the full pipeline for evaluation. If you specified "
|
|
"frozen components, make sure they were already initialized and "
|
|
"trained. Full pipeline: {pipeline}")
|
|
E901 = ("Failed to remove existing output directory: {path}. If your "
|
|
"config and the components you train change between runs, a "
|
|
"non-empty output directory can lead to stale pipeline data. To "
|
|
"solve this, remove the existing directories in the output directory.")
|
|
E902 = ("The sentence-per-line IOB/IOB2 file is not formatted correctly. "
|
|
"Try checking whitespace and delimiters. See "
|
|
"https://spacy.io/api/cli#convert")
|
|
E903 = ("The token-per-line NER file is not formatted correctly. Try checking "
|
|
"whitespace and delimiters. See https://spacy.io/api/cli#convert")
|
|
E904 = ("Cannot initialize StaticVectors layer: nO dimension unset. This "
|
|
"dimension refers to the output width, after the linear projection "
|
|
"has been applied.")
|
|
E905 = ("Cannot initialize StaticVectors layer: nM dimension unset. This "
|
|
"dimension refers to the width of the vectors table.")
|
|
E906 = ("Unexpected `loss` value in pretraining objective: '{found}'. Supported values "
|
|
"are: {supported}")
|
|
E908 = ("Can't set `spaces` without `words` in `Doc.__init__`.")
|
|
E909 = ("Expected {name} in parser internals. This is likely a bug in spaCy.")
|
|
E910 = ("Encountered NaN value when computing loss for component '{name}'.")
|
|
E911 = ("Invalid feature: {feat}. Must be a token attribute.")
|
|
E912 = ("Failed to initialize lemmatizer. Missing lemmatizer table(s) found "
|
|
"for mode '{mode}'. Required tables: {tables}. Found: {found}.")
|
|
E913 = ("Corpus path can't be None. Maybe you forgot to define it in your "
|
|
".cfg file or override it on the CLI?")
|
|
E914 = ("Executing {name} callback failed. Expected the function to "
|
|
"return the nlp object but got: {value}. Maybe you forgot to return "
|
|
"the modified object in your function?")
|
|
E915 = ("Can't use score '{name}' to calculate final weighted score. Expected "
|
|
"float or int but got: {score_type}. To exclude the score from the "
|
|
"final score, set its weight to null in the [training.score_weights] "
|
|
"section of your training config.")
|
|
E916 = ("Can't log score for '{name}' in table: not a valid score ({score_type})")
|
|
E917 = ("Received invalid value {value} for `state_type` in "
|
|
"TransitionBasedParser: only 'parser' or 'ner' are valid options.")
|
|
E918 = ("Received invalid value for vocab: {vocab} ({vocab_type}). Valid "
|
|
"values are an instance of `spacy.vocab.Vocab` or True to create one"
|
|
" (default).")
|
|
E919 = ("A textcat `positive_label` '{pos_label}' was provided for training "
|
|
"data that does not appear to be a binary classification problem "
|
|
"with two labels. Labels found: {labels}")
|
|
E920 = ("The textcat's `positive_label` setting '{pos_label}' "
|
|
"does not match any label in the training data or provided during "
|
|
"initialization. Available labels: {labels}")
|
|
E921 = ("The method `set_output` can only be called on components that have "
|
|
"a Model with a `resize_output` attribute. Otherwise, the output "
|
|
"layer can not be dynamically changed.")
|
|
E922 = ("Component '{name}' has been initialized with an output dimension of "
|
|
"{nO} - cannot add any more labels.")
|
|
E923 = ("It looks like there is no proper sample data to initialize the "
|
|
"Model of component '{name}'. To check your input data paths and "
|
|
"annotation, run: python -m spacy debug data config.cfg "
|
|
"and include the same config override values you would specify "
|
|
"for the 'spacy train' command.")
|
|
E924 = ("The '{name}' component does not seem to be initialized properly. "
|
|
"This is likely a bug in spaCy, so feel free to open an issue: "
|
|
"https://github.com/explosion/spaCy/issues")
|
|
E925 = ("Invalid color values for displaCy visualizer: expected dictionary "
|
|
"mapping label names to colors but got: {obj}")
|
|
E926 = ("It looks like you're trying to modify `nlp.{attr}` directly. This "
|
|
"doesn't work because it's an immutable computed property. If you "
|
|
"need to modify the pipeline, use the built-in methods like "
|
|
"`nlp.add_pipe`, `nlp.remove_pipe`, `nlp.disable_pipe` or "
|
|
"`nlp.enable_pipe` instead.")
|
|
E927 = ("Can't write to frozen list. Maybe you're trying to modify a computed "
|
|
"property or default function argument?")
|
|
E928 = ("An InMemoryLookupKB can only be serialized to/from from a directory, "
|
|
"but the provided argument {loc} points to a file.")
|
|
E929 = ("Couldn't read InMemoryLookupKB from {loc}. The path does not seem to exist.")
|
|
E930 = ("Received invalid get_examples callback in `{method}`. "
|
|
"Expected function that returns an iterable of Example objects but "
|
|
"got: {obj}")
|
|
E931 = ("Encountered {parent} subclass without `{parent}.{method}` "
|
|
"method in component '{name}'. If you want to use this "
|
|
"method, make sure it's overwritten on the subclass.")
|
|
E940 = ("Found NaN values in scores.")
|
|
E941 = ("Can't find model '{name}'. It looks like you're trying to load a "
|
|
"model from a shortcut, which is obsolete as of spaCy v3.0. To "
|
|
"load the model, use its full name instead:\n\n"
|
|
"nlp = spacy.load(\"{full}\")\n\nFor more details on the available "
|
|
"models, see the models directory: https://spacy.io/models and if "
|
|
"you want to create a blank model, use spacy.blank: "
|
|
"nlp = spacy.blank(\"{name}\")")
|
|
E942 = ("Executing `after_{name}` callback failed. Expected the function to "
|
|
"return an initialized nlp object but got: {value}. Maybe "
|
|
"you forgot to return the modified object in your function?")
|
|
E943 = ("Executing `before_creation` callback failed. Expected the function to "
|
|
"return an uninitialized Language subclass but got: {value}. Maybe "
|
|
"you forgot to return the modified object in your function or "
|
|
"returned the initialized nlp object instead?")
|
|
E944 = ("Can't copy pipeline component '{name}' from source '{model}': "
|
|
"not found in pipeline. Available components: {opts}")
|
|
E945 = ("Can't copy pipeline component '{name}' from source. Expected "
|
|
"loaded nlp object, but got: {source}")
|
|
E947 = ("`Matcher.add` received invalid `greedy` argument: expected "
|
|
"a string value from {expected} but got: '{arg}'")
|
|
E948 = ("`Matcher.add` received invalid 'patterns' argument: expected "
|
|
"a list, but got: {arg_type}")
|
|
E949 = ("Unable to align tokens for the predicted and reference docs. It "
|
|
"is only possible to align the docs when both texts are the same "
|
|
"except for whitespace and capitalization. The predicted tokens "
|
|
"start with: {x}. The reference tokens start with: {y}.")
|
|
E952 = ("The section '{name}' is not a valid section in the provided config.")
|
|
E953 = ("Mismatched IDs received by the Tok2Vec listener: {id1} vs. {id2}")
|
|
E954 = ("The Tok2Vec listener did not receive any valid input from an upstream "
|
|
"component.")
|
|
E955 = ("Can't find table(s) {table} for language '{lang}' in "
|
|
"spacy-lookups-data. Make sure you have the package installed or "
|
|
"provide your own lookup tables if no default lookups are available "
|
|
"for your language.")
|
|
E956 = ("Can't find component '{name}' in [components] block in the config. "
|
|
"Available components: {opts}")
|
|
E957 = ("Writing directly to `Language.factories` isn't needed anymore in "
|
|
"spaCy v3. Instead, you can use the `@Language.factory` decorator "
|
|
"to register your custom component factory or `@Language.component` "
|
|
"to register a simple stateless function component that just takes "
|
|
"a Doc and returns it.")
|
|
E958 = ("Language code defined in config ({bad_lang_code}) does not match "
|
|
"language code of current Language subclass {lang} ({lang_code}). "
|
|
"If you want to create an nlp object from a config, make sure to "
|
|
"use the matching subclass with the language-specific settings and "
|
|
"data.")
|
|
E959 = ("Can't insert component {dir} index {idx}. Existing components: {opts}")
|
|
E960 = ("No config data found for component '{name}'. This is likely a bug "
|
|
"in spaCy.")
|
|
E961 = ("Found non-serializable Python object in config. Configs should "
|
|
"only include values that can be serialized to JSON. If you need "
|
|
"to pass models or other objects to your component, use a reference "
|
|
"to a registered function or initialize the object in your "
|
|
"component.\n\n{config}")
|
|
E962 = ("Received incorrect {style} for pipe '{name}'. Expected dict, "
|
|
"got: {cfg_type}.")
|
|
E963 = ("Can't read component info from `@Language.{decorator}` decorator. "
|
|
"Maybe you forgot to call it? Make sure you're using "
|
|
"`@Language.{decorator}()` instead of `@Language.{decorator}`.")
|
|
E964 = ("The pipeline component factory for '{name}' needs to have the "
|
|
"following named arguments, which are passed in by spaCy:\n- nlp: "
|
|
"receives the current nlp object and lets you access the vocab\n- "
|
|
"name: the name of the component instance, can be used to identify "
|
|
"the component, output losses etc.")
|
|
E965 = ("It looks like you're using the `@Language.component` decorator to "
|
|
"register '{name}' on a class instead of a function component. If "
|
|
"you need to register a class or function that *returns* a component "
|
|
"function, use the `@Language.factory` decorator instead.")
|
|
E966 = ("`nlp.add_pipe` now takes the string name of the registered component "
|
|
"factory, not a callable component. Expected string, but got "
|
|
"{component} (name: '{name}').\n\n- If you created your component "
|
|
"with `nlp.create_pipe('name')`: remove nlp.create_pipe and call "
|
|
"`nlp.add_pipe('name')` instead.\n\n- If you passed in a component "
|
|
"like `TextCategorizer()`: call `nlp.add_pipe` with the string name "
|
|
"instead, e.g. `nlp.add_pipe('textcat')`.\n\n- If you're using a custom "
|
|
"component: Add the decorator `@Language.component` (for function "
|
|
"components) or `@Language.factory` (for class components / factories) "
|
|
"to your custom component and assign it a name, e.g. "
|
|
"`@Language.component('your_name')`. You can then run "
|
|
"`nlp.add_pipe('your_name')` to add it to the pipeline.")
|
|
E967 = ("No {meta} meta information found for '{name}'. This is likely a bug in spaCy.")
|
|
E968 = ("`nlp.replace_pipe` now takes the string name of the registered component "
|
|
"factory, not a callable component. Expected string, but got "
|
|
"{component}.\n\n- If you created your component with"
|
|
"with `nlp.create_pipe('name')`: remove `nlp.create_pipe` and call "
|
|
"`nlp.replace_pipe('{name}', 'name')` instead.\n\n- If you passed in a "
|
|
"component like `TextCategorizer()`: call `nlp.replace_pipe` with the "
|
|
"string name instead, e.g. `nlp.replace_pipe('{name}', 'textcat')`.\n\n"
|
|
"- If you're using a custom component: Add the decorator "
|
|
"`@Language.component` (for function components) or `@Language.factory` "
|
|
"(for class components / factories) to your custom component and "
|
|
"assign it a name, e.g. `@Language.component('your_name')`. You can "
|
|
"then run `nlp.replace_pipe('{name}', 'your_name')`.")
|
|
E969 = ("Expected string values for field '{field}', but received {types} instead. ")
|
|
E970 = ("Can not execute command '{str_command}'. Do you have '{tool}' installed?")
|
|
E971 = ("Found incompatible lengths in `Doc.from_array`: {array_length} for the "
|
|
"array and {doc_length} for the Doc itself.")
|
|
E972 = ("`Example.__init__` got None for '{arg}'. Requires Doc.")
|
|
E973 = ("Unexpected type for NER data")
|
|
E974 = ("Unknown {obj} attribute: {key}")
|
|
E976 = ("The method `Example.from_dict` expects a {type} as {n} argument, "
|
|
"but received None.")
|
|
E977 = ("Can not compare a MorphAnalysis with a string object. "
|
|
"This is likely a bug in spaCy, so feel free to open an issue: "
|
|
"https://github.com/explosion/spaCy/issues")
|
|
E978 = ("The {name} method takes a list of Example objects, but got: {types}")
|
|
E980 = ("Each link annotation should refer to a dictionary with at most one "
|
|
"identifier mapping to 1.0, and all others to 0.0.")
|
|
E981 = ("The offsets of the annotations for `links` could not be aligned "
|
|
"to token boundaries.")
|
|
E982 = ("The `Token.ent_iob` attribute should be an integer indexing "
|
|
"into {values}, but found {value}.")
|
|
E983 = ("Invalid key(s) for '{dict}': {key}. Available keys: "
|
|
"{keys}")
|
|
E984 = ("Invalid component config for '{name}': component block needs either "
|
|
"a key `factory` specifying the registered function used to "
|
|
"initialize the component, or a key `source` key specifying a "
|
|
"spaCy model to copy the component from. For example, `factory = "
|
|
"\"ner\"` will use the 'ner' factory and all other settings in the "
|
|
"block will be passed to it as arguments. Alternatively, `source = "
|
|
"\"en_core_web_sm\"` will copy the component from that model.\n\n{config}")
|
|
E985 = ("Can't load model from config file: no [nlp] section found.\n\n{config}")
|
|
E986 = ("Could not create any training batches: check your input. "
|
|
"Are the train and dev paths defined? Is `discard_oversize` set appropriately? ")
|
|
E989 = ("`nlp.update()` was called with two positional arguments. This "
|
|
"may be due to a backwards-incompatible change to the format "
|
|
"of the training data in spaCy 3.0 onwards. The 'update' "
|
|
"function should now be called with a batch of Example "
|
|
"objects, instead of `(text, annotation)` tuples. ")
|
|
E991 = ("The function `nlp.select_pipes` should be called with either a "
|
|
"`disable` argument to list the names of the pipe components "
|
|
"that should be disabled, or with an 'enable' argument that "
|
|
"specifies which pipes should not be disabled.")
|
|
E992 = ("The function `select_pipes` was called with `enable`={enable} "
|
|
"and `disable`={disable} but that information is conflicting "
|
|
"for the `nlp` pipeline with components {names}.")
|
|
E993 = ("The config for the nlp object needs to include a key `lang` specifying "
|
|
"the code of the language to initialize it with (for example "
|
|
"'en' for English) - this can't be None.\n\n{config}")
|
|
E997 = ("Tokenizer special cases are not allowed to modify the text. "
|
|
"This would map '{chunk}' to '{orth}' given token attributes "
|
|
"'{token_attrs}'.")
|
|
E999 = ("Unable to merge the Doc objects because they do not all share "
|
|
"the same `Vocab`.")
|
|
E1000 = ("The Chinese word segmenter is pkuseg but no pkuseg model was "
|
|
"loaded. Provide the name of a pretrained model or the path to "
|
|
"a model and initialize the pipeline:\n\n"
|
|
'nlp.tokenizer.initialize(pkuseg_model="default")')
|
|
E1001 = ("Target token outside of matched span for match with tokens "
|
|
"'{span}' and offset '{index}' matched by patterns '{patterns}'.")
|
|
E1002 = ("Span index out of range.")
|
|
E1003 = ("Unsupported lemmatizer mode '{mode}'.")
|
|
E1004 = ("Missing lemmatizer table(s) found for lemmatizer mode '{mode}'. "
|
|
"Required tables: {tables}. Found: {found}. Maybe you forgot to "
|
|
"call `nlp.initialize()` to load in the data?")
|
|
E1005 = ("Unable to set attribute '{attr}' in tokenizer exception for "
|
|
"'{chunk}'. Tokenizer exceptions are only allowed to specify "
|
|
"ORTH and NORM.")
|
|
E1007 = ("Unsupported DependencyMatcher operator '{op}'.")
|
|
E1008 = ("Invalid pattern: each pattern should be a list of dicts. Check "
|
|
"that you are providing a list of patterns as `List[List[dict]]`.")
|
|
E1010 = ("Unable to set entity information for token {i} which is included "
|
|
"in more than one span in entities, blocked, missing or outside.")
|
|
E1011 = ("Unsupported default '{default}' in `doc.set_ents`. Available "
|
|
"options: {modes}")
|
|
E1012 = ("Entity spans and blocked/missing/outside spans should be "
|
|
"provided to `doc.set_ents` as lists of Span objects.")
|
|
E1013 = ("Invalid morph: the MorphAnalysis must have the same vocab as the "
|
|
"token itself. To set the morph from this MorphAnalysis, set from "
|
|
"the string value with: `token.set_morph(str(other_morph))`.")
|
|
E1014 = ("Error loading DocBin data. It doesn't look like the data is in "
|
|
"DocBin (.spacy) format. If your data is in spaCy v2's JSON "
|
|
"training format, convert it using `python -m spacy convert "
|
|
"file.json .`.")
|
|
E1015 = ("Can't initialize model from config: no {value} found. For more "
|
|
"information, run: python -m spacy debug config config.cfg")
|
|
E1016 = ("The operators 'OP': '?', '*', and '+' are not supported in "
|
|
"DependencyMatcher token patterns. The token pattern in "
|
|
"RIGHT_ATTR should return matches that are each exactly one token "
|
|
"long. Invalid pattern:\n{node}")
|
|
E1017 = ("A Doc object requires both 'deps' and 'heads' for dependency "
|
|
"parses. If no dependency labels are available, provide "
|
|
"placeholder deps such as `deps=[\"dep\"]*len(heads)`.")
|
|
E1018 = ("Knowledge base for component '{name}' is not set. "
|
|
"Make sure either `nel.initialize` or `nel.set_kb` "
|
|
"is called with a `kb_loader` function.")
|
|
E1019 = ("`noun_chunks` requires the pos tagging, which requires a "
|
|
"statistical model to be installed and loaded. For more info, see "
|
|
"the documentation:\nhttps://spacy.io/usage/models")
|
|
E1020 = ("No `epoch_resume` value specified and could not infer one from "
|
|
"filename. Specify an epoch to resume from.")
|
|
E1021 = ("`pos` value \"{pp}\" is not a valid Universal Dependencies tag. "
|
|
"Non-UD tags should use the `tag` property.")
|
|
E1022 = ("Words must be of type str or int, but input is of type '{wtype}'")
|
|
E1023 = ("Couldn't read EntityRuler from the {path}. This file doesn't "
|
|
"exist.")
|
|
E1024 = ("A pattern with {attr_type} '{label}' is not present in "
|
|
"'{component}' patterns.")
|
|
E1025 = ("Cannot intify the value '{value}' as an IOB string. The only "
|
|
"supported values are: 'I', 'O', 'B' and ''")
|
|
E1026 = ("Edit tree has an invalid format:\n{errors}")
|
|
E1027 = ("AlignmentArray only supports slicing with a step of 1.")
|
|
E1028 = ("AlignmentArray only supports indexing using an int or a slice.")
|
|
E1029 = ("Edit tree cannot be applied to form.")
|
|
E1030 = ("Edit tree identifier out of range.")
|
|
E1031 = ("Could not find gold transition - see logs above.")
|
|
E1032 = ("`{var}` should not be {forbidden}, but received {value}.")
|
|
E1033 = ("Dimension {name} invalid -- only nO, nF, nP")
|
|
E1034 = ("Node index {i} out of bounds ({length})")
|
|
E1035 = ("Token index {i} out of bounds ({length})")
|
|
E1036 = ("Cannot index into NoneNode")
|
|
E1037 = ("Invalid attribute value '{attr}'.")
|
|
E1038 = ("Invalid JSON input: {message}")
|
|
E1039 = ("The {obj} start or end annotations (start: {start}, end: {end}) "
|
|
"could not be aligned to token boundaries.")
|
|
E1040 = ("Doc.from_json requires all tokens to have the same attributes. "
|
|
"Some tokens do not contain annotation for: {partial_attrs}")
|
|
E1041 = ("Expected a string, Doc, or bytes as input, but got: {type}")
|
|
E1042 = ("`enable={enable}` and `disable={disable}` are inconsistent with each other.\nIf you only passed "
|
|
"one of `enable` or `disable`, the other argument is specified in your pipeline's configuration.\nIn that "
|
|
"case pass an empty list for the previously not specified argument to avoid this error.")
|
|
E1043 = ("Expected None or a value in range [{range_start}, {range_end}] for entity linker threshold, but got "
|
|
"{value}.")
|
|
E1044 = ("Expected `candidates_batch_size` to be >= 1, but got: {value}")
|
|
E1045 = ("Encountered {parent} subclass without `{parent}.{method}` "
|
|
"method in '{name}'. If you want to use this method, make "
|
|
"sure it's overwritten on the subclass.")
|
|
E1046 = ("{cls_name} is an abstract class and cannot be instantiated. If you are looking for spaCy's default "
|
|
"knowledge base, use `InMemoryLookupKB`.")
|
|
E1047 = ("`find_threshold()` only supports components with a `scorer` attribute.")
|
|
E1048 = ("Got '{unexpected}' as console progress bar type, but expected one of the following: {expected}")
|
|
E1049 = ("No available port found for displaCy on host {host}. Please specify an available port "
|
|
"with `displacy.serve(doc, port=port)`")
|
|
E1050 = ("Port {port} is already in use. Please specify an available port with `displacy.serve(doc, port=port)` "
|
|
"or use `auto_select_port=True` to pick an available port automatically.")
|
|
E1051 = ("'allow_overlap' can only be False when max_positive is 1, but found 'max_positive': {max_positive}.")
|
|
E1052 = ("Unable to copy spans: the character offsets for the span at "
|
|
"index {i} in the span group do not align with the tokenization "
|
|
"in the target doc.")
|
|
E1053 = ("Both 'min_length' and 'max_length' should be larger than 0, but found"
|
|
" 'min_length': {min_length}, 'max_length': {max_length}")
|
|
E1054 = ("The text, including whitespace, must match between reference and "
|
|
"predicted docs when training {component}.")
|
|
E1055 = ("The 'replace_listener' callback expects {num_params} parameters, "
|
|
"but only callbacks with one or three parameters are supported")
|
|
E1056 = ("The `TextCatBOW` architecture expects a length of at least 1, was {length}.")
|
|
E1057 = ("The `TextCatReduce` architecture must be used with at least one "
|
|
"reduction. Please enable one of `use_reduce_first`, "
|
|
"`use_reduce_last`, `use_reduce_max` or `use_reduce_mean`.")
|
|
|
|
|
|
# Deprecated model shortcuts, only used in errors and warnings
|
|
OLD_MODEL_SHORTCUTS = {
|
|
"en": "en_core_web_sm", "de": "de_core_news_sm", "es": "es_core_news_sm",
|
|
"pt": "pt_core_news_sm", "fr": "fr_core_news_sm", "it": "it_core_news_sm",
|
|
"nl": "nl_core_news_sm", "el": "el_core_news_sm", "nb": "nb_core_news_sm",
|
|
"lt": "lt_core_news_sm", "xx": "xx_ent_wiki_sm"
|
|
}
|
|
|
|
|
|
# fmt: on
|
|
|
|
|
|
class MatchPatternError(ValueError):
|
|
def __init__(self, key, errors):
|
|
"""Custom error for validating match patterns.
|
|
|
|
key (str): The name of the matcher rule.
|
|
errors (dict): Validation errors (sequence of strings) mapped to pattern
|
|
ID, i.e. the index of the added pattern.
|
|
"""
|
|
msg = f"Invalid token patterns for matcher rule '{key}'\n"
|
|
for pattern_idx, error_msgs in errors.items():
|
|
pattern_errors = "\n".join([f"- {e}" for e in error_msgs])
|
|
msg += f"\nPattern {pattern_idx}:\n{pattern_errors}\n"
|
|
ValueError.__init__(self, msg)
|